Methods for processing, optimization, calibration and display of measured dielectrometry signals using property estimation grids

ABSTRACT

A method is disclosed for processing, optimization, calibration, and display of measured dielectrometry signals. A property estimator is coupled by way of instrumentation to an electrode structure and translates sensed electromagnetic responses into estimates of one or more preselected properties or dimensions of the material, such as dielectric permittivity and ohmic conductivity, layer thickness, or other physical properties that affect dielectric properties, or presence of other lossy dielectric or metallic objects. A dielectrometry sensor is disclosed which can be connected in various ways to have different effective penetration depths of electric fields but with all configurations having the same air-gap, fluid gap, or shim lift-off height, thereby greatly improving the performance of the property estimators by decreasing the number of unknowns. The sensor geometry consist of a periodic structure with, at any one time, a single sensing element that provides for multiple wavelength within the same sensor footprint.

RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.10/040,797, filed Jan. 7, 2002, which is a divisional of U.S.application Ser. No. 09/310,507, filed May 12, 1999, which claims thebenefit of Provisional Application No. 60/085,201, filed May 12, 1998,the entire teachings of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION

The technical field of this invention is dielectrometry and, inparticular, the electromagnetic interrogation of materials of interestto deduce their physical, chemical, geometric, or kinematic properties.The disclosed invention applies to semiconducting, both lossy andlossless dielectric media, very thin metalizations, and shape/proximitymeasurements for conducting and dielectric objects and surfaces.

Dielectric sensors are commonly used for material propertycharacterization and defect detection in a material under test (MUT).The sensors respond to the absolute properties of the MUT, such as theelectrical permittivity, electrical conductivity, thickness, andproximity, and changes in those properties. Factors that affect thedielectric properties include composition, chemistry and the state ofcure, density, porosity, and contamination with other substances such asmoisture. The property variations may be a normal part of themanufacturing process or a result of the presence of defects or damage.These defects can be created during the manufacturing process, such asimproper curing or incorrect layer thickness for stratified media, orwhen the material is placed into service by use- and/or age-relateddegradation processes, such as fatigue. In manufacturing, the continuingdrive toward defect-free products, yield improvement and operation nearthe capability limits of the production system require sensingtechnologies for monitoring as many critical process variables aspossible. In operations, service maintenance, and repair and replacementactivities, the continuing push toward a retirement-for-cause philosophyfrom the retire-for-time approach requires reliable measurements on allfatigue-critical components in the system, even at difficult-to-accesslocations.

Dielectric measurements can be performed with a wide variety of devices.The simplest devices involve parallel plate capacitors where the MUT isplaced between a pair of electrodes. Often guard electrodes are used tominimize the effects of fringing electric fields at the electrode edgesso that MUT is exposed to an essentially uniform electric field. Theelectrical terminal admittance or impedance of the device is thenrelated to the material properties through geometric factors associatedwith the sensor geometry.

In many applications both sides of the MUT are not easily accessible andsingle-sided sensor configurations are required. A common implementationof a single-sided sensor is the interdigitated electrode structure usedfor chemical and moisture sensing applications. U.S. Pat. No. 4,814,690further discloses the use of multiple sets of interdigitated electrodesas part of the imposed frequency-wavenumber dielectrometry approach forspatial profiling of stratified dielectric media. These devices havebeen effective in determining the dielectric properties of fluids.However, the determination of solid dielectric properties is morecomplicated due to the presence of microcavities or unintentional airgaps between the solid dielectric and the sensor.

While one can attempt to compensate for the air gap, the thickness isusually unknown and variable across the surface of the sensor.Therefore, effective compensation may be difficult to achieve even withmultiple sensors placed onto a single substrate. One of the difficultiesis due to the fact that a sensor having a number of sensor elements,each with different electrode spacings, those sensor elements are notco-located and therefore are not located at exactly the same placesrelative to the MUT.

Generally dielectrometry measurements require solving of an inverseproblem relating the sensor response to the physical variables ofinterest. Such inverse parameter estimation problems generally requirenumerical iterations of the forward problem, which can be very timeconsuming often preventing material identification in real-time.Real-time parameter estimations often need to be provided for suchapplications as manufacturing quality control. In some cases, simplecalibration procedures can be applied, but these suffer from requiringand assuming independent knowledge about the properties. More advancedmodel-based techniques utilize multivariable parameter estimationalgorithms to estimate the properties of interest, but these aregenerally slow, precluding real-time measurement capabilities, and maynot converge on the desired solution.

SUMMARY OF THE INVENTION

The present invention comprises of a method for generating propertyestimates of one or more preselected properties or dimensions of amaterial. Specific embodiments of the methods are disclosed forgenerating, calibrating, measuring properties with, and selecting amongtwo-dimensional response databases, called measurement grids, for bothsingle wavelength dielectrometry applications and multiple wavelengthdielectrometry applications.

One step in a preferred method requires defining or estimating the rangeand property estimate tolerance requirements for the preselectedproperties or dimensions of the material under test. The next step isthe selecting at least one of each of an electrode geometry,configuration, excitation source, and measurement instrument operatingpoint. A continuum model, either analytical or numerical or anexperimental approach using calibration test pieces of known propertiesand dimensions or both are then used to generate measurement grids aswell as operating point response curves for preselected operating pointparameters.

The measurement grids and operating point response curves aresubsequently analyzed to define a measurement strategy. Operating pointparameters and an electrode geometry, configuration, and excitationsource are then determined to meet the dynamic range and tolerancerequirements. To accomplish this, property estimation grids andoperating point response curves are generated and analyzed for variousoperating points. The sensitivity and selectivity is calculated forgrids representing varying electrode designs and operating conditions.Then the best of the lot of prechosen design parameters and operatingconditions are selected. If inadequate to requirements, this evaluationprocess can be reiterated with improved selections based on what waslearned in prior rounds.

A property estimator implements a model for generating a propertyestimation grid, which translates sensed responses into preselectedmaterial property or dimension estimates. Accordingly, the presentinvention includes a method for generating a property estimation gridfor use with a dielectrometer for estimating preselected properties ordimensions of a material under test. The first step in generating a gridis defining physical and geometrical properties of the MUT and theelectrode geometry, configuration, and source excitation for thedielectrometer are defined.

The material properties, the operating point parameters, and thedielectrometer electrode geometry, configuration, and source excitationare input into a model to compute an input/output terminal relationvalue. In a preferred embodiment, the input/output terminal relation isa value of transadmittance magnitude and phase. The terminal relationvalue is then recorded and the process is repeated after incrementingthe preselected properties of the material under test. After a number ofiterations, the terminal relation values are saved in a database ofmaterial responses and plotted to form a property estimation grid.

A preferred embodiment of the method according to the invention includesthe incorporation of geometric properties into the grid databases forthe representation of multi-layered media and the use of analyticproperties of the measurement grid to map from measurement space toproperty space, such as singular value decomposition, condition numbers(and visualizations of these), to improve selection amongst alternativesensor designs and operating conditions. In addition, the preferredembodiment uses methods for measuring with and calibratingdielectrometers, using single and multiple grids for multiple wavenumberdielectrometry Exploiting the characterization and understanding ofother properties of such mappings to aid in choosing and selecting amongmeasurement grid alternatives is also feasible.

A preferred method of the invention includes enhancing sensitivity andselectivity by using fluids or solids of known properties and dimensionsto intentionally move the sensor response within the grid or to alterthe grid itself. Movement within grids can also be achieved by varyingother parameters such as temperature that also affect permittivity. Themethod supports both measurement and calibration. One method uses“shims” of known dielectric constant, conductivity, and thicknessbetween the sensor and the material under test.

The need is also recognized for a sensor device configuration thatreduce the sensor sensitivity to undesired inhomogenities across theface of the sensor. In a preferred embodiment, a sensor has multipleelectric field penetration depths but each with the same air-gap, fluidgap, or shim lift-off height, thereby greatly reducing the number ofunknowns in parameter estimation algorithms.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescription of preferred embodiments of the invention, as illustrated inthe accompanying drawings in which like reference characters refer tothe same parts throughout the different views. The drawings are notnecessarily to scale, emphasis instead being placed upon illustratingthe principles of the invention.

FIG. 1 is an overall schematic diagram of an apparatus for measuring theelectrical, physical, and geometrical properties of a material undertest according to the present invention;

FIG. 2 is a representative single wavelength interdigitated electrodedielectrometer with spatially periodic driven and sensing electrodes ofwavelength λ that can measure dielectric properties of the adjacentmaterial;

FIGS. 3A and 3B show two IDED sensors with different electrodewavelengths and illustrates that the penetration depth of electric fieldinto the material is proportional to the wavelength;

FIG. 4 illustrates a three wavelength sensor on a single substrate witheach sensor having a different wavelength;

FIG. 5A shows a property estimation grid for measurement of dielectricpermittivity epsilon and ohmic conductivity sigma for a single 2.5 mmwavelength sensor;

FIG. 5B shows the parameter space of complex permittivity, ε*=ε′−jε″, ina uniform medium j=√{square root over (−1)} which allows calculation ofε′ and ε″ from gain/phase dielectrometry measurements. In the plots ε′and ε″ are normalized to the dielectric permittivity of free space,ε₀≈8.854E−12 farads/meter, so that the numerical values are relativepermittivities;

FIG. 6 shows the property estimation grid of dielectric permittivityepsilon and lift-off air gap thickness using a 1 mm and 2.5 mm twowavelength sensor;

FIG. 7 shows a property estimation grid for the dielectric permittivityand thickness of a dielectric layer sandwiched between two dielectricshaving known properties and over an insulating substrate;

FIG. 8 shows transient measurements of the dielectric properties of twocuring epoxies plotted against a measurement grid;

FIG. 9 shows the transient measurement of the permittivity as twoepoxies cure;

FIG. 10 shows the transient measurement of the conductivity as twoepoxies cure;

FIG. 11 shows a magnitude-phase grid for a single wavelength sensor,where the parameters being measured are permittivity and conductivity;

FIG. 12 shows a grid used when a non-contact measurement of a material'spermittivity is performed;

FIG. 13 shows a grid used to measure a dielectric coating layer'sthickness and permittivity in a contact measurement;

FIG. 14 shows a grid which uses phase information from two separatesensors to estimate conductivity and permittivity of a material;

FIG. 15 shows how the dielectric permittivity of a solid material can bemeasured using two identical sensors with variable liquid mixtures ofknown permittivity to fill any air gaps;

FIG. 16 is a generalized procedure flow diagram for the estimation ofmaterial under test properties and measurement tolerances according tothe present invention;

FIG. 17 is a flow diagram of the generation of a property estimationgrid using a continuum model according to the invention;

FIG. 18A illustrates a dielectrometry sensor having three sets ofelectrodes which alternate roles of drive, sense, and guard electrodes;

FIG. 18B is a schematic of the dielectrometry sensor of FIG. 18A and aswitching device connected to an admittance analyzer;

FIG. 19 shows the calculated capacitance per meter versus air-gaplift-off height of the three configurations of the sensor in FIG. 18whereby the electrode widths are all 500 μm, and the distance betweenelectrode centerlines in a half-wavelength is 2470 μm (FN), 1530 μm(NS), and thus 4000 μm (FS);

FIG. 20 normalizes the calculated capacitance curves in FIG. 19 to thedifference between zero distance and infinite distance; and

FIG. 21 shows the calculated capacitance grids of near to sense (NS)electrodes as a function of air lift-off height in mm and relativepermittivity for the 8 mm wavelength sensor dimensions given in FIG. 19.

DETAILED DESCRIPTION OF THE INVENTION

Methods, techniques, and devices are disclosed for measurements ofelectrical, physical, and dimensional properties of a material undertest as well as geometric and kinematic properties of the measurementarrangement. These measurements are made with both contact andnon-contact of the material under test by a sensor. For contactmeasurements, the sensor may be embedded in material under test (MUT).

A measurement apparatus 30 is illustrated in FIG. 1. The measurementapparatus 30 includes an electromagnetic element 32 comprised of voltagedriven electrode 34, voltage or current sensing electrode 36, adielectric substrate 38 that is preferably highly electricallyinsulating, and a highly conducting back plane 40.

The driven electrode 34 has an imposed electrical excitation, typicallyeither a voltage or current that can be either periodically varying intime such as sinusoidally or square wave varying with time at frequencyf measured in Hertz for frequency domain measurements or can be anon-repetitive voltage or current signal such as a step, pulse, orimpulse for time domain measurements. Measurement of the electricalresponse, typically voltage or current, induced in the sensing electrode36 allows calculation or measurement of the transadmittance (or transferadmittance, or alternatively the transimpedance, or complex gain (i.e.,either a Vout/Vin or Iout/Iin measure) between sensing and drivenelectrodes. The transadmittance is measured by the admittance analyzer44 or an impedance analyzer.

The measurement apparatus 30 is connected to an analyzer 42. Theanalyzer 42 has an admittance analyzer 44 and a property estimator 46.Either the current Is or the voltage, Vs, of the sensing electrode orsome combination of the two can be used in this measurement. Themagnitude 48 and phase 50 of measured transadmittances, which isgenerated by the admittance analyzer 44, are used to estimatepre-selected properties or dimensions of a single, multiple layered, orcontinuously stratified material under test 52. The properties ordimensions are estimated, using a property analyzer 56 of the propertyestimator 46. The property analyzer 56 of the property estimator 46interacts with a measurement grid 58 of the property estimator. Themeasurement grid 58 represents properties of the material. Themeasurement grid 58 can be generated with continuum analytical ornumerical models 60 or through experimental measurements on calibrationtest pieces with known geometry and electrical properties or both. Anexample of a measurement grid 58 is shown in FIGS. 5A, 5B, 6-8, 11-14,and 21 and disclosed in U.S. Pat. No. 5,453,689, Sep. 26, 1995, titled“Magnetometer Having Periodic Winding Structure and Material PropertyEstimator,” the entire contents of which are incorporated herein byreference. The model 60, measurement grid(s) 58, and property analyzer56 are part of the property estimator 46 that converts measurements atthe sensor terminals for single or multiple operating points (e.g.multiple temporal excitation frequencies or multiple types of timevarying waveforms) to estimate pre-selected material under testproperties or dimensions of interest.

Through proper design and selection of the electromagnetic elements 32,methods for proper selection of operating point(s) parameters andmethods for selection of measurement details, e.g., instruments andtheir operating points, choice of measured values, grids used increasesensitivity, selectivity, and dynamic and other ranges of propertyestimation.

This increased capability through the selection of the elements, points,and properties as explained below results in measurement of propertiesand or dimensions of interest for the material under test which are notmeasurable with traditional electrode structures.

The grid measurement methods provide a real-time capability for solvingthe inverse problem relating the material properties to the sensorresponse. These grid measurement methods use a database of sensorresponses to map the measured signals into the desired properties forthe material. The database is derived, prior to the data acquisition,using a “forward model” of the sensor response using either a continuummodel or a finite element or other numerical method for the sensor andthe specific problem of interest and/or a preselected set of calibrationexperiments. The measurement databases can be visualized as grids, asseen in FIG. 13, that relate measured parameters, such as the magnitudeand phase of the impedance, to the unknown parameters, such as thepermittivity and thickness of a dielectric layer.

These measurement methods are applied to capacitive sensingdielectrometry, where the dielectric properties of a material can bedescribed by two parameters, the permittivity and conductivity. Thepermittivity is a constitutive parameter that relates the displacementcurrent density in the material to the applied electric field, whereasthe conductivity applies to the conduction current density. Thedielectric properties of materials vary significantly and can provide ameans for characterization of the materials and their geometricproperties such as size or layer thickness.

It is convenient to represent the complex permittivity of a material asε*=ε′−jε″, where ε′ is the real part and ε″ is the imaginary part of thecomplex permittivity. The real part is the dielectric constant, orpermittivity, of the material (ε′=ε); whereas, the imaginary part(ε″=σ/ω where σ is the conductivity and ω is the angular frequency ofthe electric field) describes the power dissipation or loss of thematerial. The dielectric spectrum of a material is a representation ofits complex permittivity, expressed as a function of frequency. Thedielectric spectrum provides a signature of a material in a particularstate.

Classical dielectrometry extracts information about the state of amaterial construct from its dielectric spectrum. The application of asinusoidally varying potential of complex magnitude v and angularfrequency ω=2πf results in the flow of a terminal current with complexamplitude I, whose magnitude and phase are dependent on the complexpermittivity of the material.

Referring to FIG. 2, an interdigitated electrode dielectrometer (IDED)capacitive sensor 70 is illustrated. The IDED 70 utilizes a pair ofinterdigitated electrodes 74 and 76 to produce a spatially periodicelectric field. The electrodes 74 and 76 are positioned in proximity tothe material of interest or under test with an insulating substrate 38and a ground plane electrode 40 on the other side of the substrate, asseen in FIG. 1. One of the two interdigitated electrodes, 74, is drivenwith a sinusoidally varying voltage, vD, (the driven electrode 34) whilethe other, 76, is connected to a known load impedance andhigh-input-impedance voltage buffer stage used to measure the magnitudeand phase of the potential, vS, (the sensing electrode 36) with respectto the driving voltage vD. The periodicity of the electrode structure isdenoted by the spatial wavelength λ=2πc/κ, where κ is the wavenumber. Aninterdigitated electrode dielectrometer (IDED) sensor is also describedin U.S. Pat. No. 4,814,690, “Apparatus and Methods for MeasuringPermittivity in Materials,” of Mar. 21, 1989, the entire contents ofwhich are incorporated herein by reference.

The depth of sensitivity of the sensor is determined by the electrodespacing. The electric scalar potential in the materials above and belowthe sensor obeys Laplace's equation. In Cartesian coordinates withlinear lossy dielectrics the potential can be written as an infiniteseries of sinusoidal Fourier modes of fundamental spatial wavelength lthat decays away in the z direction $\begin{matrix}{{\Phi( {y,z} )} = {\sum\limits_{n = 0}^{\infty}{\Phi_{n}{{\mathbb{e}}^{{- k_{n}}z}( {{A_{n}\quad\sin\quad k_{n}y} + {B_{n}\quad\cos\quad k_{n}y}} )}}}} & (1)\end{matrix}$where k_(n)=2πn/λ is the wavenumber of mode n. The periodicity of theelectrode structure leads to sinusoidal variations in the y directionand exponential decay in the z direction for penetration into thedielectric MUT. For every mode the decay rate in the z direction isequal to the wavenumber k_(n) of the variations in the y direction.

FIGS. 3A and 3B illustrates two sensors 80 and 82. Each sensor showsdriven electrodes 34 and sensing electrodes 36. Sensor 80 shown in FIG.3A, has a distance between the electrodes 34 and 36 of λ₁ (awavelength), wherein the distance between the electrodes 34 and 36 areillustrated as less and λ₂ in FIG. 3B. The electric field 84 penetrationdepth into a material under test (MUT) increases with increasing sensorwavelength.

A three wavelength sensor 86 is shown in FIG. 4. The sensor 86 has threedistinct sensors 88, 90, and 92. Each sensor is an IDED sensor with adriven electrode and a sensing electrode. In a preferred embodiment, thewavelength of the sensors 88, 90, and 92 are 2.5 mm, 5 mm, and 1 mmrespectively. The three wavelength sensor is used for heterogeneousmedia, spatial profiles of dielectric properties or layer thickness.

Measurement of the gain and phase, the real and imaginary parts of thetransadmittance between the driven and the sensing electrodes, or thetransconductance and transcapacitance, provides two parameters which canbe related to conductivity and dielectric permittivity of a material.Liquid and gaseous dielectrics are most suitable for this type ofmeasurement because the fluid conforms to the sensor surface. Thiseliminates the uncertainty in geometry that can exist for measurementswith solid dielectrics due to surface roughness and deformation of thesolid material and sensor electrodes. Alternatively, thecomb-serpentine-comb structure disclosed herein allows for improvedaccuracy in the determination of the properties of solid dielectrics byallowing different depths of penetration to be achieved within the samesensor footprint. An alternative method to achieve multiple sensingwavelengths is disclosed in U.S. patent application Ser. No. 09/003,390,filed on Jan. 6, 1998 titled “Magnetometer and Dielectrometer Detectionof Subsurface Objects,” the entire contents of which are incorporatedherein by reference.

FIG. 5A shows a property estimation grid generated for 2.5 mm wavelengthinterdigital sensor immersed in a liquid dielectric. The properties ofthe liquid dielectric are to be estimated. The liquid dielectric, whoseproperties can range from semi-insulating (such as mineral oil) toconducting (such as aqueous solutions), flows around the sensor andallows for intimate contact between the sensor, the surfaces and MUT.The total sensing electrode length was assumed to be 0.5 m. Variation ofthe calculated conductance and capacitance with the properties of thedielectric is reflected in the grid by plotting lines of constantdielectric permittivity “epsilon” and conductivity “sigma”. In thisexample, the conductivity is dependent on temperature while thepermittivity has negligible variation with temperature. The dielectricproperties are monitored as temperature changes. Several measurementpoints are indicated on the grid in FIG. 5A with the “*” sign. Theexperimental points fall along a constant “epsilon” line indicatingchanges in “sigma” only. The measured values of “sigma” can be obtainedby interpolating between constant “sigma” grid lines.

While property grids for the real and imaginary parts of the complexpermittivity for semi-infinite materials have been generated,measurement grids have not been incorporated into the design oroperation of dielectrometry measurement systems. The property grids forsemi-infinite material have been used to illustrate the mapping betweenthe model response and the measured response, but the inverse problem ofestimating the properties of the material under test use iterativeprocedures which minimize the error (for example, the least squareerror) between the measure response and the response for estimateparameter. In contrast, the method of the invention uses measurementgrids to estimate properties of the material under test. Different formsof measurement grids are required to solve specific problems. Themeasurement grids express two properties relative to each other. Forexample, FIG. 7 shows measurement grids for variations in thepermittivity and thickness of a curing polymer layer sandwich betweentwo protective layers and the mapping into the measureable quantities ofsensor transcappacitance and thickness. This measurement grid is used insuch cure state monitoring of a coating with using an independentdetermination of thickness. An example of a property grid is shown inFIG. 8, which shows the variations of the permittivity and conductivityof a test material (MUT) placed above a protective layer and an IDEDsensor and the mapping into measurable sensor magnitude and phase.

The incorporation of geometric properties into the grids for therepresentation of multi-layered media, methods for measuring with andcalibrating dielectrometers, the use of single and multiple grids formultiple wavenumber dielectrometry, and the use of singular valuedecomposition and condition numbers to improve selection amongstalternative grids and grid representation candidates, as describedbelow. This invention also includes new methods for enhancingsensitivity and selectivity by using fluids or solids of knownproperties and dimensions to intentionally move the sensor responsewithin the grid. Movement within grids, i.e., shifting of operatingpoints, can also be achieved by varying other parameters such astemperature that also affect permittivity.

For general dielectrometry measurements of homogeneous solids, there areusually at least three unknowns that need to be determined: the materialdielectric constant and conductivity and an unknown air-gap thicknessbetween sample and sensor. This air gap can be intentional in the caseof noncontact measurements or it can be the unintentional result ofvoids between the sample and the sensor due to sample roughness anddeformation. Although these voids are usually quite small, on the orderof a few micron spacing for smooth samples and greater for roughsamples, the voids are located in the region of strong electric fieldand consequently have a significant effect on the sensor response. Witha device containing two wavelength sensors, each wavelength provides twoindependent measurements of gain and phase, so that in most cases thefour measured values give more than enough information necessary toevaluate the three unknowns. With more wavelengths, the additionalredundant information can be used to further improve parameterestimations via mathematical fits, such as using a least squares fitbetween theory and measurements, or using single or multiple measurementgrids at each frequency and averaging the results. For nonhomogeneousdielectrics, other physical parameters of interest may be the layerthickness, porosity, moisture content, or anisotropic propertyvariations.

In some situations it is possible to simplify the measurements of thesolid MUT's dielectric properties by either eliminating one of theunknown parameters or operating the sensor in a regime that isindependent of one of the material properties. In the simplest case, theair gap may be negligible for a contact measurement if, for example, theMUT is fluid or soft enough to conform the sensor geometry. Then asingle wavelength measurement of the transcapacitance andtransconductance yields the effective permittivity and conductivity ofthe MUT, as in FIG. 5A. In cases where the air gap cannot be neglected,the material properties can be inferred from independent measurementswith two sensors with different wavelengths if the sensors operate in atemporal frequency regime where the measurements are independent of theeither the dielectric constant or the conductivity. For example, at highfrequencies such that the measured admittance is only capacitive thenthe sensors only respond to the permittivity and thicknesses of the airgap and the MUT. Shorter wavelength sensors are more sensitive to thethickness of the air gap region, while longer wavelength sensors havefields that penetrate further into the MUT to be more sensitive to thedielectric properties of the MUT. A plot of the measured capacitancesfor each wavelength results in a unique measure of the MUT permittivityand equivalent air gap thickness.

FIG. 6 shows a measurement grid generated for a 1 and 2.5 mm wavelengthsensors, both with 0.5 m total sensor electrode length. Here, a twoindependent spatial wavelength, high temporal frequency measurement canprovide independent values for the air gap lift-off thickness and thepermittivity of the MUT.

In another implementation, a single wavelength sensor can be used incombination with information from other sources to provide estimates ofthe solid MUT's dielectric properties. In this generalization of themeasurement grid approach, variations in a dielectric or geometricproperty of the MUT are mapped into two measurable parameters, only oneof which is from a conventional dielectrometry measurement ofcapacitance or conductance. The other measurable parameter, such as alayer thickness, temperature, or pressure, is an input from some othersensing device. As an example, consider a nonhomogeneous MUT consistingof four layers of insulating polymers, with the only unknown parametersbeing the permittivity and the thickness of the second layer away fromthe sensor. This represents, for example, a curing polymer layersandwiched between two protective films and placed onto an insulatingsubstrate. A representative measurement permittivity-thickness grid,with simulated data, is shown in FIG. 7. The expected ranking of thesample data is indicated by the circled numbers in FIG. 7. It is assumedthat the thickness of the unknown layer could be measured with anotherdevice such as a micrometer. In this case, simply using thetranscapacitance to infer the permittivity of the cure layer would givean incorrect ranking (2, 1, 4, 3) because of the variations in the layerthickness. Using the measurement grids to compensate for the thicknessvariations allows the proper ranking of the samples (1, 2, 3, 4) to bedetermined. It should thus be clear from this example that themeasurement grids do not need to be based on a measurements from asingle sensor (such as capacitance and conductance) or a single type ofsensor (capacitance at one wavelength versus capacitance at a secondwavelength) but rather that any combination of measurement parameters ispossible.

One example application that illustrates the grid measurement approachis the curing of epoxies as shown in FIG. 8. In these measurements, athick layer of epoxy was placed on a 2.5 mm wavelength sensor that wascovered with a thin protective polymer layer. As the epoxy cures thedielectric properties change, with both the permittivity andconductivity generally decreasing as the cure becomes more complete. Themeasured sensor impedance for both a 5 and 15 minute epoxy is plotted onthe measurement grid in FIG. 8. The actual transients for the epoxydielectric properties, estimated from the measurement grid are shown inFIG. 9 for the permittivity and FIG. 10 for the conductivity. In bothcases the dielectric properties change rapidly until the nominal settime is reached, after which the dielectric properties change at aslower rate. The polymer layer covered the sensor to protect the sensorand allow its reuse. In order to get accurate measurements of the epoxyproperties, the measurement grids accounted for the properties of thislayer. With the measurement grid created prior to data acquisition, theinversion from the measured transadmittance to the dielectric propertiescan be performed in real-time as part of a quality control application.Several other grids are presented to illustrate some variations on thisapproach, where different types of grids are generated to fit the needsof a particular application.

FIG. 11 shows a single wavelength sensor grid which can be used tomeasure the permittivity and conductivity of a material. Withsignificant conductivity present there is information in the phase ofthe signal which can be used to estimate two quantities independentlywith a single sensor.

In cases where the materials are insulating, the magnitude values fortwo separate sensors are used in a two-dimensional grid to estimatepermittivity, thickness, lift-off, or other geometric parameters withtwo unknowns. Examples of such magnitude-magnitude grids are shown inFIG. 12 and FIG. 13. The grid in FIG. 12 is used to perform non-contactmeasurements of the permittivity of a dielectric coating, which is thenrelated to other physical properties, such as cure state, porosity, etc.The grid method makes it possible to simultaneously measure the distancebetween the sensor head and the MUT. This is useful in providing areal-time signal which can then be used in the control of the headpositioning system so that a constant separation between the sensor andthe sample is maintained, e.g. when the sample is in motion. On theother hand, the fact that the lift-off is being estimated independentlyshows that with this grid method the measured material property isindependent of the exact position of the sensor.

In a related operation, FIG. 13 shows a grid used in contactmeasurements. It is a magnitude-magnitude grid, where the two materialproperties being varied are the permittivity and thickness of thecoating layer. In cases where the thickness of the coating may not beindependently measured, or where this thickness is another qualitycontrol characteristic that needs to be monitored, this method providesindependent information for these two MUT properties.

FIG. 14 illustrates a different embodiment of the method whereby resultsfrom two different dielectric sensors are combined in a single grid. Inthis case phase of both sensors are used instead of phase and magnitudeof one sensor.

In the case of a single wavelength measurement, only two measurementvalues (gain and phase) are determined, which are insufficient touniquely determine three or more unknowns. A well-calibrated shim ofknown permittivity, conductivity and thickness can be inserted betweensensor and sample; placed on the other side of the sample; or multipleprecisely positioned shims including air gaps can be used. Thegain/phase measurement can be repeated for any combination of these shimvariations. The shim can be either solid or a fluid (liquid or gas)located between the solid MUT and the sensor. One embodiment of a liquidshim is described below with respect to FIG. 15. Multiple measurementscan be performed for various thickness shims or for shims placed atvarious locations using a precision positioning system such as that of apiezoelectric precision positioning system. These two or moreindependent measurements are now sufficient to estimate the variousunknowns. When well-calibrated shims are used with multi-wavelengthsensors, the additional redundant data can be used with improved signalprocessing methods with multi-dimensional grids.

A variation of the calibrated shim measurement method is to use liquiddielectrics of well known permittivity, conductivity and thickness withtwo identical sensors. One sensor has an unknown dielectric while thesecond sensor uses well-calibrated known dielectrics. Well characterizedmiscible liquid dielectrics of precisely controlled volume are added tothe calibrated sensor until the gain/phase results match those from theunknown dielectric measurement, so that geometric and physicalproperties of the unknown dielectric can be determined from comparisonto measurements of known dielectrics.

FIG. 15 illustrates this concept with measurement of the dielectricpermittivity of a solid material of arbitrary shape immersed in a liquiddielectric using two identical sensors. One is pressed against the solidtest specimen, and one is immersed in the dielectric liquid. The liquidis electrically homogeneous at all times, and it can easily flow to fillin any void regions with the solid specimen. Initially, the dielectricpermittivity of the liquid is lower than that of the solid, whichresults in the lower capacitance between the electrodes of the sensorimmersed in the liquid. As a second miscible liquid with a higherdielectric permittivity is being added to the first liquid, thecapacitance of both sensors increases. However, the capacitance of theliquid only sensor increases at a higher rate because it responds to thechanges of properties in the entire volume, while the solid/sensorsystem only responds to the changes in properties of the relativelysmall void regions. At a certain point, the two capacitances becomeidentical. This point corresponds to the condition that the liquidmixture dielectric permittivity equals the solid dielectricpermittivity.

Generalized Material Under Test Property Estimation Framework

The method and techniques of the disclosed invention comprise a generalproperty estimation framework. This approach is related to the onedeveloped by Goldfine et al. in U.S. Pat. No. 5,629,621, “Apparatus andMethods for Obtaining Increased Sensitivity, Selectivity and DynamicRange in Property Measurements using Magnetometers,” the entire contentsof which are incorporated herein by reference. The application todielectometry as opposed to magneometry is complicated by differences inboth the nature of the sensing techniques and differences in theresponses of materials. In magnetometry, the decay of the sensing fieldinto the material is governed by the (vector) magnetic diffusionequation, which has partial derivatives with respect to both time andspace. In contrast, dielectometry is governed by the (scalar) Laplace'sequation, which has only partial derivatives with respect to space.Thus, achieving multiple spatial decay rates with magnetometry requireschanging only the temporal frequency of excitation. Achieving this samecapability for dielectometry requires specific designs in the electrodestructures, as described both above and further below.

Similarly, there are differences in responses of materials; not allmaterials have strong magnetic or conducting responses required tointeract with magnetometers, but all materials have some dielectricresponse. Therefore, air-gap lift-off layers, which are mere separationlayers in magnetometry have more direct influence in dielectometry,which complicates the application to measurements of solids, due to theinavoidable, and typically non-uniform, sensor lift-off. Many other, butless troublesome differences exist, which are well known to those versedin both arts, magnetometry and dielectometry, which preclude themechanical transferrance of methods from one domain to the other. Theunavoidable lift-off layer is one of if not the most troublesome inapplying this methodology to measurements of properties of solids, soseveral means of overcoming this obstacle are disclosed herein.

A typical measurement procedure flow would include the following stepsas shown in the procedure flow diagram in FIG. 16:

-   Step 1 (102): Define material under test (MUT) property measurement    requirements-define the dynamic range and measurement tolerance    requirements for the MUT properties of interest.-   Step 2 (104): Select sensor electrode geometry, configuration,    substrate material and dimensions, and source excitation (e.g. for    the periodic electrode structure in FIG. 1 select the structure,    shape, and design of the driven 34 and sensing 36 electrodes, the    substrate 38, and the conducting back plane 40 geometry). Selection    is based on test and evaluation of property estimation sensitivity,    dynamic range, and selectivity, using the predicted responses and    measurement grids 58 generated by the continuum model 60 and/or    through experimental measurements on calibrated test pieces over the    required range of properties for a variety of electrode geometries,    substrate materials, dimensions, and configurations.-   Step 3 (106): Analyze the property estimation grids and operating    point responses to define the measurement strategy-the measurement    strategy includes the number of measurements required at different    operating points and with different sensor geometries, substrate    materials, dimensions, and configurations. A continuum model 60    and/or set of experiments on calibration pieces is used to generate    property estimation grids (i.e., databases) 58 and a set of response    curves which are functions of operating point parameter variations.    Operating point response curves include (1) the standard temporal    frequency or time domain response, and responses to (2) variations    in the defined electrode geometry or for the case of periodic    structures the spatial wavelength of the sensor electrode construct.    The defined spatial wavelength λ, the wavelength of the dominant    eigenfunction, or fundamental Fourier component, in the electric    scalar potential distribution and imposed along the surface of the    MUT; the defined spatial wavelength can be adjusted in actual    measurements by including several similar electrode constructs, each    with a different defined spatial wavelength as defined in U.S. Pat.    No. 4,814,690. It can also be adjusted by use of non-maximally    symmetric sensors, such as shown in FIG. 18, together with varying    the electrode pair (e.g., NS vs. NF vs. FS pairings) used for the    measurement. (3) the relative position and kinematics of the    electrode construct to the MUT including the height above or below    the MUT surface, the position along the surface, the orientation    relative to the surface, tilt angle and motion, and (4) adjusting    the geometry of the electrode construct (including the distance    between the driven and sensing electrodes), the relationship between    the driving and sensing electrode widths to the wavelength A; the    relative position of the backplane 40 to the electrode plane; and in    the case of nonlinear, anisotropic, or bianisotropic media the    magnitude, direction, and spatial or temporal variation of an    applied DC or AC bias electric and/or magnetic fields.-   Step 4 (108): Determine useable and/or optimal operating point(s)    and electrode dimensions-a set of operation point parameters, for    one operating point, includes the proximity to the MUT, the temporal    frequency, and all other adjustable parameters described in Step 3    (106). Singular value decomposition on the Jacobian matrix, relating    variations in the transadmittance magnitude and phase to variations    in the MUT properties of interest, is used when an accurate    continuum analytical or numerical model is available to determine    the relative performance potential at different operating points. If    such a model is not available a set of carefully designed    calibration experiments can be used, along with models of related    electrode and MUT geometries to provide additional insight. Relative    performance potential includes sensitivity to variations in the MUT    properties of interest, selectivity for pairs of properties of    interest, and dynamic range for each property of interest. Then    parameter estimation grids 58, also referred to as measurement    grids, are generated at optimal/selected operating points along with    operating point response curves for use in property estimation in    Step 6 (112).-   Step 5 (110): Execute measurement strategy. Measure the    transadmittance at each prescribed operating point defined in the    measurement strategy, using the admittance analyzer 44.-   Step 6 (112): Estimate the preselected MUT properties-estimate the    MUT properties of interest, using, for example, root-searching    techniques, trial and error, table look up and interpolation; and/or    graphical interpolation from measurement grids 58 generated with    simulations, i.e. continuum model, 60 and/or calibration    experiments. This is accomplished in the property estimator 46.-   Step 7 (114): Estimate the property estimation tolerances-using    measurement grids 58 and operating point response curves generated    with the continuum model 60 (or calibration experiments) and the    measurement tolerances and tolerance variations over the dynamic    range of interest for each pre-selected MUT property of interest. If    the property estimation measurement requirements are not achieved    (116), repeat Steps 2 (104) through 7 (114).

For any application, calibration experiments can be used to tune themodel parameters and improve MUT property estimation accuracy. Suchcalibration, although not always required, should always be used whenavailable.

Property Estimation Grid Database and Operating Point Response CurveGeneration

Each parameter estimation application will require a set of propertyestimation grids, i.e., databases/measurement grids 58 and operatingpoint response curves. The number of grids and response curves requiredwill depend on the application. The grids and response curves haveseveral different uses throughout the parameter estimation process.These uses include the following:

-   1) Develop a measurement strategy and select the measurement    operating points by evaluating the MUT property estimation grids and    operating points response curves, at a variety of different    operating points over the required dynamic range for the MUT    properties of interest (Step 3 (106): of the generalized MUT    property estimation procedure in FIG. 16). Evaluating a property    estimation grid includes investigating the sensitivity, selectivity    and dynamic range for the MUT properties of interest. This is first    accomplished by visually inspecting the grids. For example, a grid    which provides a large variation in the magnitude and phase of the    transcapacitance in response to relatively small variation in the    MUT properties of interest would provide a good property estimation    performance. This is discussed further in the next section, where    the use of singular value decomposition is described as an automated    method for identifying the “best” operating points, as well as    determining the dynamic range over which sensitivity requirements    can be met for measurement of specific MUT properties of interest.-   2) Graphical estimation of the MUT properties of interest (Step 6    (112): of the generalized MUT property estimation procedure in FIG.    16). For example, in FIG. 5A for a 2.5 mm wavelength IDED structure,    the transcapacitance and transconductance are calculated over a    range of conductivities and permittivities, while in FIG. 6 the    transcapacitances are calculated for 1 mm and 2.5 mm wavelength IDED    structures over a range of permittivities and lift-off distances.    The conductivity and permittivity for the case of FIG. 5A or the    permittivity and lift-off distance for the case of FIG. 6 are then    estimated from each measurement for FIG. 5 or pair or measurements    for FIG. 6. Alternatively, the grids are used to obtain first    guesses for the conductivity, permittivity, or lift-off distance and    then the parameter estimated values are adjusted until the least    squares error between the measured transcapacitance and/or    transconductance and the response for the estimated permittivity,    conductivity or lift-off is minimized.-   3) Determination of the estimate tolerances, as a function of the    estimated values for the MUT properties of interest (Step 7 (114):    of the generalized MUT property estimation procedure in FIG. 16).    The tolerances at a given grid point are estimated by averaging the    variation in transadmittance magnitude and phase between that grid    point and its neighboring grid points and dividing both by the    average change in magnitude and the average change in phase into the    corresponding change in the MUT property of interest. For example,    if a change in dielectric thickness of 1 mm causes a phase change of    10 degrees, the sensitivity is 1 degree per 0.1 mm. If the    admittance analyzer 44 can accurately measure phase to 0.1 degrees    then a 0.1 degree change in transadmittance phase would correspond    to a 0.01 mm change in thickness. In other words, the limit on the    measurement precision for dielectric thickness for this example    would be 0.01 mm (the actual tolerances will vary significantly with    operating point specifications, MUT properties, and electrode    construct, geometry, and dimensions). Also, the value of the    measurement tolerance will vary with the MUT property estimate value    over the dynamic range for the MUT properties of interest. The    reported measurement tolerance should also include the effects of    other inherent errors due to unmodelled dynamics. These errors could    be determined for each sensor and model, using calibration test    pieces.-   4) Provide comparison and evaluation of measurement strategy    options. All too often measurements are performed with inadequate    understanding of whether the measurement strategy (a.k.a., protocol,    methodolgy) is adequate to the task, what properties the strategy    has, whether such properties of the strategy could be improved or    are already optimal. In situations where measurements of certain    kinds have been needed for years, or decades, ad-hoc standards and    rules of thumb have often accumulated. Often they are sanctified by    various standards bodies. In the absence of means of evaluating and    comparing measurement strategies, this is the best that can be    expected. But in measurement domains where means of evaluating and    comparing measurement strategies have been developed, ad-hocracy has    been supplanted with objective evaluation. This has occurred long    since for many simple measurements, e.g., circuit measurement of    voltage or impedance. The methods disclosed herein, and their    obvious extensions, now enable the choice of dielectometry    measurement strategies to be made on objective scientific bases,    instead of rules of thumb and ad-hoc techniques. It is the analysis    of the properties of measurement grids and operating response    curves, such as condition numbers and singular value decompositions,    when applied to comparison and selection of measurement strategies    and the details that comprise such strategies, that enables    objective comparisons and rational choices.

FIG. 17 provides a flow diagram describing the generation of a propertyestimation grid or measurement grid 58, using an analytical or numericalcontinuum model 60. The same concepts described in this figure apply tothe generation of operating point response curves. The only differenceis that for property estimation grids the main loop is repeated fordifferent MUT property pairs (e.g. permittivity and conductivity,permittivity and lift-off or conductivity and lift-off), while for thegeneration of operating point response curves one operating pointparameter is varied over a range of interest (i.e. an operating pointresponse curve is generated by computing the transadmittance responsefor each incremented value of one operating point parameter, with allother operating point parameters held constant). An operating pointresponse curve is generally a one-dimensional grid, where the variableis an adjustable operating point parameter (e.g., lift-off, frequency,or wavelength) instead of a preselected MUT property (two-dimensionalgrids that permit properties to vary, e.g., lift-off and wavelength, arealso valuable). The air gap lift-off height is generally considered anoperating point parameter. However, in many applications it is moreconvenient to consider the lift-off eight as a MUT property of interest.

Fringing Field Multi-Penetration Depth Dielectrometry Sensor with CommonLift-Off Height

The property estimators with multi-penetration depth dielectrometrysensors can be most accurate if the lift-off height for each electrodeconfiguration is the same. This can be achieved with a three electrodefringing field dielectrometry sensor 120 shown in FIG. 18A. Each set offiner electrodes 122, 124, and 126 can be used sequentially as drive,sense, and guard electrodes. The electrode 122 and the electrode 126 aremultifingered and are arranged with the multifingers of the electrode122 interdigitated with the multifingers of the electrode 126. Theelectrode 124 meanders between the two interdigitated electrodes 122 and126. Even though the fundamental spatial wavelength of eachconfiguration is the same, the relative amplitudes of each of thespatial harmonics will change with each configuration. To maximize thedifference in harmonic amplitudes and thereby maximally change theeffective penetration depths of the electric field, it is best tomaximize the distances from the center electrode to the electrodes oneither side. One way to calculate this optimum spacing is to use a“golden section”. If the sensing electrode is in the center (such as 124in FIG. 18A), donate the electrode on one side (such as 126 in FIG. 18A)a distance x away as “far” and the electrode on the opposite side (suchas 122 in FIG. 18A) a distance a−x as “near”, so that the distance from“far” to “near” electrodes is a, then a “golden section” is defined suchthat x is the geometric mean of a and a−x, x=[a(a−x)]^(1/2) so thatx=a(√5−1)/2≈0.618a. With this “golden section”, the ratio of distance of“far” to “sense” (FS) electrodes to “sense” to “near” (NS) electrodesequals the distance ratio of “far” to “near” (FN) electrodes to “far” to“sense” (FS) electrodes, the ratio being≈1.618.

The configuration of FIG. 18A is significantly different than thoseproposed in the prior art. U.S. Pat. No. 4,814,690 by Melcher et al.discloses switching the individual elements of the interdigitatedstructure between driven and sensing to vary the fundamental wavelengthof the measurement, this requires a switch for every element in thesensor, while the configuration of FIG. 18 only requires switches to beplaced at the terminals. The configuration of FIGS. 18A and 18B switchesthe roles of the drive, sense, and guard electrodes to intentionallyvary the penetration depths of the electric field. A switching device130 connects the sensor 120 to the admittance analyzer 44

The sensor topology of FIG. 18A was used with electrode widths of 500μm; FN centerline distance of 2470 μm, NS centerline distance of 1530μm, and thus a FS centerline distance 4000 μm; substrate thickness of254 μm; electrode thickness of 17 μm, substrate relative permittivity of2.2; and a relative permittivity of an adjacent dielectric of 3.0. FIG.19 shows the calculated capacitance variation with air-gap lift-offheight for each possible pair of electrodes (NS, FS, FN). To compare thevariations for each of the electrode configurations it is convenient tonormalize the capacitances to the difference of capacities at zerolift-off (no air-gap) to infinite life-off height (all air-gap) as shownin FIG. 20. The effective penetration depth can be defined as thatlift-off height when the capacitance reached 97% if its infinitelift-off height value, as shown by the 97% line in FIG. 20. As seen inFIG. 20 the effective penetration depths are then 570 μm (NS), 1180 μm(FN), and 2020 μm (FS).

FIG. 21 shows the calculated grid for a loss-free dielectric for an 8 mmwavelength sensor with the dimensions of the previously describeddesign. The grid shows how from measurements of the “FS” and “NS”capacitances, the air-gap lift-off height in μm and dielectricpermittivity can be determined. For example, if the measured near tosense capacitance is 12 pF and the measured far to sense capacitance is1.4 pF, then plotting the measured value on the grid of FIG. 21 andinterpolating along the grid lines gives property estimates of 35 μm forthe lift-off and 3.8 for the relative permittivity.

While this invention has been particularly shown and described withreferences to preferred embodiments thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the spirit and scope of theinvention as defined by the appended claims.

1. A method for generating and evaluating property estimation grids foruse with a dielectrometer that provides at least two effective fieldpenetration depths for measuring preselected properties of a material,said method comprising: a) defining electrical, physical, and geometricproperties for the material, including preselected properties of thematerial; b) defining operating point parameters for the materialproperties and an electrode geometry, electrode configuration, substratematerial and dimensions, and electrical source excitation for thedielectrometer; c) inputting the material properties, the operatingpoint parameters, and the dielectrometer electrode substrate geometry,configuration and source excitation into a model to compute a terminalrelation value for each penetration depth; d) recording in a databasethe terminal relation value for each penetration depth relative to thematerial properties as a property estimation grid point; e) adjustingthe preselected material properties and repeating steps (c) and (d) forremaining property estimation grid points; and f) analyzing a propertyestimation grid to determine fitness of the property estimation grid fora particular measurement.
 2. A method as claimed in claim 1 wherein theterminal relation value of step (c) is at least one of: transcapacitancevalue, transconductance value, transadmittance value, transimpedancevalue, self-admittance value, self-impedance value, and complex gain. 3.A method as claimed in claim 1 wherein the material comprises a liquidmixture of unknown properties.
 4. A method as claimed in claim 1 whereinone or more of the operating point parameters in parts b) and c) aresingle or multiple shims of known property and geometry.
 5. A method asclaimed in claim 1 further comprising: the step of plotting terminalrelation values on a single or multidimensional grid.
 6. A method asclaimed in claim 1 wherein the grid points represent magnitude and phasemeasurements for a single wavelength dielectric sensor.
 7. A method asclaimed in claim 1 wherein the property estimation grids aremagnitude-magnitude grids with the magnitudes determined from differentfield penetration depths.
 8. A method as claimed in claim 7 wherein themagnitude-magnitude grids are used for measurements performed on asemi-insulating material.
 9. A method for generating and evaluatingproperty estimation grids for use with a dielectrometer for measuringpreselected properties of a material, said method comprising: a)defining electrical, physical, and geometric properties for thematerial, including preselected properties of the material; b) definingoperating point parameters for the material properties and an electrodegeometry, electrode configuration, substrate material and dimensions,and electrical source excitation for the dielectrometer; c) inputtingthe material properties, the operating point parameters, and thedielectrometer electrode substrate geometry, configuration and sourceexcitation into a model to compute a terminal relation value for each ofa dielectric sensor and a non-dielectric sensor; d) recording in adatabase the terminal relation value for each sensor relative to thematerial properties as a property estimation grid point; e) adjustingthe preselected material properties and repeating steps (c) and (d) forremaining property estimation grid points; and f) analyzing a propertyestimation grid to determine fitness of the property estimation grid fora particular measurement, one axis of a property estimation gridrepresenting a magnitude or phase measured with a dielectric sensor anda second axis representing a parameter measured with a non-dielectricsensor.
 10. A method as claimed in claim 1 wherein one or more of theoperating point parameters for the material properties in steps (b) and(c) is temperature dependent and wherein variations in the temperatureare used to alter at least one operating point parameter.
 11. A methodas claimed in claim 1, further comprising: computing Jacobian elementswhich are measures of variation in computed terminal relation values dueto variation in the preselected material properties; computing asingular value decomposition for the Jacobian elements to obtainsingular values, singular vectors and condition numbers of the Jacobianelements; evaluating at least one of: the dielectrometer electrode,substrate structures and operating point using the singular values,singular vectors, and the condition numbers for material propertyestimate requirements; adjusting at least one of: the dielectrometeroperating point parameters, electrode geometry, configuration, substratematerial and geometry, and the source excitation; and repeating steps(b)-(f) until material property estimate requirements are achieved. 12.A method as claimed in claim 11 wherein the singular values, singularvectors, and the condition numbers are stored with grid points.
 13. Amethod as claimed in claim 11, further comprising: converting eachsensed electromagnetic response into a transadmittance or transimpedancemagnitude and phase or equivalently into real and imaginary parts.
 14. Amethod as claimed in claim 1 wherein the material under test is composedat least in part of a viscous material.
 15. A method as claimed in claim14 wherein the viscous material is curable.
 16. A method as claimed inclaim 14 wherein the material is monitored as part of a quality controlprocess. 17-26. (canceled)
 27. A method as claimed in claim 1 whereinthe property estimation grids are phase-phase grids.
 28. A method asclaimed in claim 9 wherein the parameter measured with a non-dielectricsensor is a thickness.
 29. A method as claimed in claim 9 wherein one ormore of operating point parameters for the material properties in steps(b) and (c) are temperature dependent and wherein variations in thetemperature are used to alter at least one operating point parameter.30-31. (canceled)